Resolving Translation Ambiguity By Ontological Chain for Cross Language Information Retrieval
碩士 === 國立交通大學 === 資訊科學系所 === 92 === Bilingual dictionaries have been commonly used for query translation in cross-language information retrieval(CLIR). However, the problem of translation ambiguity happens in query translation. Recent studies suggest traversing WordNet for selecting appropriate tran...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2004
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| Online Access: | http://ndltd.ncl.edu.tw/handle/73784787270503597835 |
| Summary: | 碩士 === 國立交通大學 === 資訊科學系所 === 92 === Bilingual dictionaries have been commonly used for query translation in cross-language information retrieval(CLIR). However, the problem of translation ambiguity happens in query translation. Recent studies suggest traversing WordNet for selecting appropriate translations. This paper proposes an ontological chain approach to resolve translation ambiguity. First, we find the most smilar ontology nodes for each query. Second, we construct a semantic graph according to the semantic distances between these nodes. And finally we select the connected component with the highest score as our ontological chain. We show that our approach reaches 81% effect of monolingual information retrieval systems. When there are many candidate translations, our system performs better than monolingual information retrieval system.
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